System and method for forecasting demanufacturing requirements

ABSTRACT

Demanufacturing workload is forecast based on anticipated volumes of equipment to be disassembled and/or salvaged, as well as equipment complexity factors determined by disassembly prototyping. Staffing requirements are unique for each customer and are based on the number of pounds needed to be worked during each month and the associated complexity (work content multiplier) for that customer&#39;s typical or expected returns.

CROSS REFERENCES TO RELATED APPLICATIONS

[0001] U.S. patent application Ser. No. 09/524,366, entitled “Method ofDemanufacturing a Product” by E. J. Grenchus, et al., contains subjectmatter related, in certain respect, to the subject matter of the presentapplication. The above-identified patent application is incorporatedherein by reference.

BACKGROUND OF THE INVENTION

[0002] 1. Technical Field of the Invention

[0003] This invention pertains to workload forecasting. Moreparticularly, it relates to workload planning for demanufacturingoperations such as dismantle and salvage.

[0004] 2. Background Art

[0005] As the life cycle of computers and other complex electricalequipment continues to decrease due to new technology and improvedprocessing performance, the useful life span of equipment has becomecorrespondingly shorter. Dismantling this equipment and salvaging usefulcomponents and materials has become imperative from both an economic andenvironmental standpoint. As a result, dismantle and salvage companiesare faced with an increasing volume and diversity of returned end oflife equipment. That is, given the varying complexity of obsoleteequipment, planning workload and staffing related to dismantle andsalvage operations presents a significant challenge. Dynamic changes arerequired by such companies to meet the required capacity in people,space, and capital equipment—all costly investments. Therefore, theperformance of demanufacturing operations becomes critical to not onlyensuring proper environmental disposal options, but also improvingprocess efficiency and minimizing expense.

[0006] It is an object of the invention to provide an improved systemand method for forecasting staffing and equipment requirements.

[0007] It is a further object of the invention to provide a system andmethod for forecasting staffing and equipment requirements for ademanufacturing enterprise.

[0008] It is a further object of the invention to provide a system andmethod for forecasting staffing and equipment requirements based oncustomer disposal plans and historical data.

SUMMARY OF THE INVENTION

[0009] A system and method for workload planning includes determiningfor each of a plurality of prospective customers, a projected volume ofmaterial for processing; determining for each customer a complexityfactor for processing the material; and responsive to the projectedvolume and complexity factor, determining staffing requirements forprocessing the material.

[0010] In accordance with an aspect of the invention, there is provideda computer program product configured to be operable to project staffingrequirements for processing material by projecting material volume,determining a complexity factor for processing that material, andresponsive to the complexity factor and volume, determining staffingrequirements.

[0011] Other features and advantages of this invention will becomeapparent from the following detailed description of the presentlypreferred embodiment of the invention, taken in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0012]FIG. 1 is a flow chart representation of a preferred embodiment ofthe method of the invention for determining workload as a function ofvolum forcasts and complexity factors.

[0013]FIG. 2 is a schematic representation of a simple algorithm forcalculating demanufacturing staffing requirements in accordance with anexemplary embodiment of the invention.

[0014]FIG. 3 is a schematic representation of the generation ofcapacity, staffing, productivity and volume workload as a functiontruck, pallet, machine, or box volume or dollar value of inventory inputto a demanufacturing process.

[0015]FIG. 4 is a schematic representation of another exemplaryembodiment of the system and method the invention.

BEST MODE FOR CARRYING OUT THE INVENTION

[0016] The present invention provides the advantage of forecastingdemanufacturing workload based on anticipated volumes of equipment, aswell as equipment complexity factors determined by disassemblyprototyping.

[0017] Anticipated equipment volumes can include such information as thetype and number of units of equipment to be dismantled. When equipmentof a certain type is received, experienced dismantlers disassemble atleast one of that type to determine an equipment complexity factor in aprocess known as disassembly prototyping. Easily disassembled equipmenttypes will have a relatively lower complexity factor, and equipmenttypes that are difficult to disassemble will have a higher complexityfactor. Salvageable and disposable content for a given equipment typewill also be determined during disassembly prototyping. Highersalvageable content will indicate a higher complexity factor as caremust be taken not to damage salvageable components during disassembly.Additional time must also be taken to properly store salvageablecomponents rather than simply disposing of them. All of this informationis then entered into a workload planning model, which calculates aworkload forecast. Staffing requirements, with regard to both hiring andresource balancing between projects, can then be based on this forecast.

[0018] In accordance with a preferred embodiment of the invention,process requirements (including staffing, capital equipment, and soforth) for a demanufacturing enterprise are defined by determining foreach customer a projected work content and dismantle complexity factor.

[0019] In accordance with a preferred embodiment of the invention, ademanufacturing workload model is used for monthly planning and in theyearly planning process. Model outputs include (1) documentation ofmonthly incoming items for demanufacturing and salvage (D&S) bycustomer; (2) manpower forecast by various categories (i.e., machines,parts, etc.) by month; (3) productivity targets and actual productivitytracked against those targets; and (4) projected pounds received anddismantled by customer by month. This model is updated and distributedperiodically, such as monthly) according to the following process. (1) Acustomers representative provides monthly projections as in put to themodel. These projections are obtained through discussions with thecustomer or analysis of past history, and may be for some period, suchas a year, into the future. (2) Data received from the customerrepresentative is input to the model, and (3) a report is generated anddistributed to process engineers, planning personnel, and management. Ingeneral, the intent of each periodic update is to provide a reasonablyaccurate outlook of the workload for the current month and an estimatefor the rest of the year. Manpower and pound processed projections areused to calculate productivity targets.

[0020] This model may be implemented as, for example, a Lotus 1-2-3spreadsheet, which facilitates periodic revision. Data regarding actualreturns received, work processed, and staffing is collected on a monthlybasis, distributed prior to the model update, and used to aid in theprojection of future volumes and workload/staffing. Staffingrequirements are unique for each customer and are based on the number ofpounds needed to be worked during each month and the associatedcomplexity (work content multiplier) for that customer's returns. Once ayear, or as required, a meeting may be held with the appropriateproduction and engineers to revisit and revise the work content criteriaused in the model.

[0021] Referring to FIG. 1, an exemplary embodiment of the method of theinvention includes the following steps.

[0022] In step 20, the enterprise interfaces with each of its customersto obtain equipment or materials disposal or processing needs andforecasts.

[0023] In step 22, the returns from new customers, or new equipment ormaterials from existing customers, are evaluated to establish adismantle complexity factor. In a preferred embodiment of the invention,this is accomplished by systematically dismantling machines asprototypes, identifying the work content and resulting items (saleableitems, commodities, trash, etc.) This data may then be input to themachine tear down model described in E. J. Grenchus, Jr. et al. U.S.Ser. No. 09/524,366 (supra).

[0024] In step 24, workload is determined by a workload determinationcomputer model as a function of complexity factor times volumeforecasts, adjusted by workforce efficiency and other factors toforecast staffing requirements and other factors, such as projectedtotal and by customer volume received and processed, workloadefficiency, and so forth. Volumes may be input as volume of scrap foreach month in pounds, pallets, truckloads, etc. The results of theworkload determination computer model include monthly forecast ofworkforce staffing requirements (by customer and total), monthlyforecast of volume (preferably represented by pounds) received andprocessed (by customer and total), monthly forecast of workforceefficiency, plan-to-actual tracking of output, and dismantle and salvage(D&S) workforce subprocess performance.

[0025] In step 26 the above results are evaluated, and in step 28 astrategy is determined for responding to workload forecast fluctuations.

[0026] In this manner, a user is able to predict future workloadfluctuations and address them with less invasive or costly solutions,resulting in greater profit, higher customer satisfaction, and a morestable workforce.

[0027] Referring to FIG. 2, an exemplary forecasting model convertsprojected customer returns to weight 85, multiplies this by thecomplexity factor described above to generate a staff requirement 88 fora particular customer. The summation of staff requirements 88 for allcustomers for a particular time period are adjusted by expectedabsenteeism factor 90, fatigue factor 91, breaks requirements 92, andvacation patterns 93 to create an adjusted staffing requirement 94 forthe enterprise.

[0028] Referring to FIG. 3, an automated tool is provided for generatingstaffing and workload answers to a complex problem, where many customersreturn different amounts of work each month, and each customer has itsown unique complexity associated with its work. This exemplaryforecasting model determines number of pounds to be addressed and thenumber of people required to do so. This may be done by convertingnumber of machines 30 from field, plant and external sources, and numberof parts 32 from field, external and internal sources, into volume 34.Volume 34 may be represented in truck loads, pallets, machines, boxes,or even dollar value of inventory, or some other equivalent measureadaptable as input to workload model 36. Volume may also be expressed asproduce or dry-goods, to deal with a situation involving the stocking ofdry-goods and produce—where dry-good stocking would be more complex thatstocking produce. Workload model 36, responsive to input 34, generatescapacity, staffing, productivity, and volume forecasts which are fed toproduction 38 and financial 40 personnel for evaluation and planningpurposes. The staffing output predicts the number of people required tostaff a job(s), and this may be customized to various countries or areas(by varying complexity, absenteeism, fatigue, breaks and vacationfactors.

[0029] An exemplary embodiment of the invention converts truck loads topounds, and applies a complexity factor to generate person hours.Conversion of volume measure (pounds, truckload, machine, or pallet,etc.) to persons hours is accomplished by generating a profile for thecustomer based initially on prototype dismantling and thereafter asmodified by experience, or actual history of hours/volume measure.

[0030] Referring to FIG. 4, a specific embodiment of the inventionprovides a workload projection model for a demanufacturing enterprisewhich has many customers 50-53. Customer representative(s) 54 determineswith each customer a plan for future shipments, arranges timing ofshipments and establishes contracts for processing those shipments.Engineer 58 receives from customer representative 54 a monthly shipmentsplan for each customer 50-53 (for example, in trucks or pounds) andmonthly updates of that plan for each established and new customer.Engineer 58 also accesses manufacturing process tracking database foractual data on previous work, or arranges for prototype dismantling togenerate complexity factors. Input 60 to the model or tool forgenerating staffing and workload projections includes projected futuredeliveries 61 for each customer, average truck weight 62 for eachcustomer, customer returns work complexity factor 63, and actualmeasurements of returns received and processed (such as by trucks orpounds, by customer) and the staffing required. Weight 62 may beestablished through discussion with the customer 50, historicalinformation derived from manufacturing process tracking database 56, orexperience (such as the experience of the customer representative 54 orengineer 58). Output 80 of the workload projection model 70 includesprojected future deliveries and volume 71 by customer, historical datamonthly and annual volume 72, projected workload and staffing 73 bycustomer and total, and production efficiency target and actuals 74.This report 80 is distributed to process engineer 81 to monitor areaworkload and worker efficiency, planner 82 to project costs, spendingand staffing, and manager 83 to monitor the plan to outlook and makestaffing decisions.

Advantages Over the Prior Art

[0031] It is an advantage of the invention that there is provided animproved system and method for forecasting staffing and equipmentrequirements.

[0032] It is a further advantage of the invention that there is provideda system and method for forecasting staffing and equipment requirementsfor a demanufacturing enterprise.

[0033] It is a further advantage of the invention that there is provideda system and method for forecasting staffing and equipment requirementsbased on customer disposal plans and historical data.

Alternative Embodiments

[0034] It will be appreciated that, although specific embodiments of theinvention have been described herein for purposes of illustration,various modifications may be made without departing from the spirit andscope of the invention. In particular, it is within the scope of theinvention to provide a computer program product or program element, or aprogram storage or memory device such as a solid or fluid transmissionmedium, magnetic or optical wire, tape or disc, or the like, for storingsignals readable by a machine, for controlling the operation of acomputer according to the method of the invention and/or to structureits components in accordance with the system of the invention.

[0035] Further, each step of the method may be executed on any generalcomputer, such as IBM Systems designated as zSeries, iSeries, xSeries,and pSeries, or the like and pursuant to one or more, or a part of oneor more, program elements, modules or objects generated from anyprogramming language, such as C++, Java, P1/1, Fortran or the like. Andstill further, each said step, or a file or object or the likeimplementing each said step, may be executed by special purpose hardwareor a circuit module designed for that purpose.

[0036] While the preferred embodiments of the invention have beendescribed with reference to planning, staffing and workload efficiencyelements of demanufacturing operations, they are also applicable to anymanufacturing or remanufacturing process, and may be adapted to D&Sworkload planning as well as to other enterprises such as manufacturersand companies where logistical control and associated manpower planningis required.

[0037] Accordingly, the scope of protection of this invention is limitedonly by the following claims and their equivalents.

We claim:
 1. A method for workload planning, comprising the steps of:determining for each of a plurality of prospective customers, aprojected quantity of material for processing; determining for eachcustomer a complexity factor for processing said material; andresponsive to said projected quantity and said complexity factor,determining staffing requirements and productivity targets for ademanufacturing enterprise for processing said material.
 2. The methodof claim 1, further comprising the step of projecting said quantity byvolume.
 3. The method of claim 1, further comprising the step ofconverting said volume to weight.
 4. The method of claim 2, furthercomprising the steps of converting said volume to weight, anddetermining said complexity factor by prototyping.
 5. The method ofclaim 4, said prototyping including the step of disassembly prototyping.6. The method of claim 5, said disassembly prototyping step beingapplied to new material and further comprising the step of accumulatinghistorical data for determining said complexity factor for previouslydisassembled material.
 7. The method of claim 2, said projecting stepfurther comprising the step of determining an expected number oftruckloads of said material.
 8. The method of claim 5, said disassemblyprototyping further including the step of determining salvageable anddisposable content for said material of a given equipment type.
 9. Themethod of claim 1, further comprising the steps of applying saidquantity projections and complexity factors to workload planning modelfor forecasting workload requirements for said processing; andresponsive to said workload requirements determining staffingrequirements and resource balancing between projects.
 10. The method ofclaim 9, further comprising the steps of adjusting said workloadrequirements for absenteeism, fatigue, breaks, and vacation patternfactors.
 11. The method of claim 9, said workload planning model beingimplemented as a computer spreadsheet.
 12. The method of claim 11,further comprising the step of periodically updating said workloadplanning model based upon actual and anticipated changes in quantityprojections and complexity factors.
 13. The method of claim 10, furthercomprising the step of calculating said productivity targets for ademanufacturing enterprise using said quantity projections andcomplexity factors.
 14. A method for forecasting staffing requirementsfor a demanufacturing enterprise, comprising the steps of: convertingprojected customer returns to weight, multiplying said weight by acomplexity factor determined by disassembly prototyping to generate astaff requirement for each of a plurality of customers; generating asummation of said staff requirements for all customers; and adjustingsaid staff requirements for all customers by an expected absenteeismfactor, fatigue factor, breaks requirements, and vacation patterns togenerate said staffing requirements and productivity targets for saiddemanufacturing enterprise.
 15. The method of claim 14, furthercomprising the step of executing said converting, generating, andadjusting steps in a spreadsheet model.
 16. System for workloadplanning, comprising: a computer model for determining for each of aplurality of prospective customers, a projected quantity of material forprocessing; a computer model for determining for each customer acomplexity factor for processing said material; and a computer model,responsive to said projected quantity and said complexity factor, fordetermining staffing requirements and productivity targets forprocessing said material.
 17. The system of claim 16, furthercomprising: a process tracking database for accumulating historicaldata, said data including actual and projected complexity factors formaterials for each of plurality of said customers.
 18. The system ofclaim 17, further comprising: model input for receiving customerprojections of said quantity of material and the results of disassemblyprototyping.
 19. A program storage device readable by a machine,tangibly embodying a program of instructions executable by a machine toperform method steps for workload planning, said method stepscomprising: determining for each of a plurality of prospectivecustomers, a projected quantity of material for processing; determiningfor each customer a complexity factor for processing said material; andresponsive to said projected quantity and said complexity factor,determining staffing requirements and productivity targets forprocessing said material.
 20. The program storage device of claim 19,said method steps further comprising the step of projecting saidquantity by volume.
 21. The program storage device of claim 19, saidmethod steps further comprising the step of converting said volume toweight.
 22. The program storage device of claim 20, said method stepsfurther comprising the step of converting said volume to weight, anddetermining said complexity factor by prototyping.
 23. The programstorage device of claim 22, said prototyping step including the step ofdisassembly prototyping.
 24. The program storage device of claim 23,said disassembly prototyping step being applied to new material andfurther comprising the step of accumulating historical data fordetermining said complexity factor for previously disassembled material.25. The program storage device of claim 20, said projecting step furthercomprising the step of determining an expected number of truckloads ofsaid material.
 26. The program storage device of claim 23, saiddisassembly prototyping further including the step of determiningsalvageable and disposable content for said material of a givenequipment type.
 27. The program storage device of claim 19, said methodsteps further comprising the steps of applying said quantity projectionsand complexity factors to workload planning model for forecastingworkload requirements for said processing; and responsive to saidworkload requirements determining staffing requirements and resourcebalancing between projects.
 28. The program storage device of claim 27,said method steps further comprising the step of adjusting said workloadrequirements for absenteeism, fatigue, breaks, and vacation patternfactors.
 29. The program storage device of claim 27, said workloadplanning model being implemented as a computer spreadsheet.
 30. Theprogram storage device of claim 29, said method steps further comprisingthe step of periodically updating said workload planning model basedupon actual and anticipated changes in quantity projections andcomplexity factors.
 31. The program storage device of claim 28, saidmethod steps further comprising the step of calculating saidproductivity targets for a demanufacturing enterprise using saidquantity projections and complexity factors.
 32. A computer programproduct or computer program element for forecasting staffingrequirements for a demanufacturing enterprise, according to the stepsof: converting projected customer returns to weight, multiplying saidweight by a complexity factor determined by disassembly prototyping togenerate a staff requirement for each of a plurality of customers;generating a summation of said staff requirements for all customers; andadjusting said staff requirements for all customers by an expectedabsenteeism factor, fatigue factor, breaks requirements, and vacationpatterns to generate said staffing requirements and productivity targetsfor said demanufacturing enterprise.